// Use when scoring finished content against quality dimensions, evaluating whether a piece meets publishable standards, or determining which workflow phase needs rework based on quality gaps.
Use when organizing raw material into a coherent structure, defining the throughline of a piece, building an outline, or making strategic decisions about what to include and cut from generated content.
Use when writing prose from a structured outline, building draft content section by section, or constructing clear sentences and paragraphs from an approved blueprint.
Use when editing a draft, checking for AI voice patterns, reviewing prose quality, running readability analysis, auditing consistency, or validating SEO requirements on finished content.
Use when brainstorming ideas, generating raw material, or starting the creative phase of a writing project. Invoke for topic exploration, idea generation, angle discovery, or producing abundant raw content before organizing.
Use when creating nonlinear outlines, generating mindmap diagrams for article structure, mapping a knowledge domain visually, or bridging raw ideas into structured options for the user to select from.
Use when planning a multi-article content strategy from a research corpus, creating domain maps for content topology, building production plans for pillar and cluster articles, or tracking cross-article production.
| name | quality-rubric |
| description | Use when scoring finished content against quality dimensions, evaluating whether a piece meets publishable standards, or determining which workflow phase needs rework based on quality gaps. |
| license | MIT |
| metadata | {"author":"https://github.com/dmitry","version":"1.0.0","domain":"quality","triggers":"quality score, rubric, evaluate content, publishable, content quality, scoring dimensions, rework routing, quality assessment, content evaluation","role":"specialist","scope":"analysis","output-format":"report","related-skills":"judge, architect, carpenter"} |
The Quality Rubric is the evaluation specialist. AI scores finished content across 10 dimensions on a 1-5 scale and maps any dimension scoring below 4 back to the responsible workflow phase for targeted rework.
Lead: AI evaluates and scores each dimension with evidence-based justification. Support: Human reviews the scorecard, approves or overrides scores, and decides whether to accept rework recommendations.
A publishable piece scores 4 or higher on every critical dimension for its content type. The Quality Rubric does not perform rework itself. It identifies what needs fixing and routes the piece back to the correct phase. The responsible phase then executes the fix under its own workflow.
This skill sits downstream of the Judge phase. The Judge handles line-level detection and polish. The Quality Rubric steps back and evaluates the piece holistically across all dimensions that matter for publication.
Receive polished draft from Judge phase -- Read the full draft, the original Architect blueprint, and any Judge detection reports. Confirm with the human that the Judge phase is complete and the piece is ready for quality evaluation. Do not score a draft that has not been through the Judge.
Score each of 10 dimensions on 1-5 scale with justification -- Evaluate the piece against all 10 scoring dimensions. For each dimension, assign a score from 1 (Poor) to 5 (Excellent) and provide a specific justification citing evidence from the text. Do not assign scores without pointing to concrete passages, patterns, or metrics. See references/scoring-dimensions.md for the full rubric.
Check scores against minimum publishable thresholds -- Look up the content type in the minimum standards table. Verify that the average score meets the minimum and that all critical dimensions for this content type score 4 or higher. See references/minimum-standards.md for thresholds by content type.
For any dimension below 4, identify responsible phase and rework action -- For each dimension that falls below the publishable threshold, identify which workflow phase owns that dimension and specify the rework action. Be precise: "return to Architect to restructure Section 3 and Section 5 ordering" is useful; "needs structural work" is not.
Present quality scorecard to human -- Deliver the complete scorecard with pass/fail assessment and rework recommendations. The human decides whether to approve publication, request rework, or override any scores. Do not initiate rework without explicit human approval.
| Topic | Reference | Load When |
|---|---|---|
| Full 10-dimension rubric with scoring levels and phase mapping | references/scoring-dimensions.md | Scoring any dimension, understanding phase responsibility |
| Minimum publishable thresholds by content type and rework routing | references/minimum-standards.md | Checking pass/fail, routing rework to phases |
MUST DO:
MUST NOT DO:
Quality Scorecard
# Quality Scorecard: [Article Title]
## Content Type: [type]
## Minimum Average Required: [n] | Actual Average: [n]
## Status: [PASS / FAIL]
## Dimension Scores
| # | Dimension | Score | Phase Responsible | Justification |
|---|-----------|-------|-------------------|---------------|
| 1 | Thesis and Argument | [1-5] | Architect | [evidence] |
| 2 | Evidence and Depth | [1-5] | Madman + Carpenter | [evidence] |
| 3 | Structure and Flow | [1-5] | Architect + Carpenter | [evidence] |
| 4 | Clarity and Readability | [1-5] | Carpenter + Judge | [evidence] |
| 5 | Voice and Authority | [1-5] | Madman + Carpenter | [evidence] |
| 6 | Opening and Hook | [1-5] | Madman + Carpenter | [evidence] |
| 7 | Conclusion and Takeaway | [1-5] | Architect + Carpenter | [evidence] |
| 8 | Technical Accuracy | [1-5] | Judge | [evidence] |
| 9 | SEO Optimization | [1-5 or N/A] | Architect + Carpenter + Judge | [evidence] |
| 10 | Originality and Value-Add | [1-5] | Madman + Pre-Research | [evidence] |
## Rework Recommendations (if FAIL)
| Dimension | Current Score | Target | Return to Phase | Specific Action |
|-----------|--------------|--------|-----------------|-----------------|
| [name] | [n] | 4 | [phase] | [what to do] |
## Summary
[1-2 sentence overall assessment and next step recommendation]
This skill extends the Madman, Architect, Carpenter, Judge framework (Betty S. Flowers, 1981) with a formal quality gate. The original framework implies evaluation at the Judge stage, but treats it as line-level editing rather than holistic scoring. The Quality Rubric adds a structured, dimension-based evaluation that maps failures back to their origin phase, preventing the common mistake of trying to fix structural problems with editorial polish.
The 10 scoring dimensions draw from established content quality frameworks including readability research, SEO best practices, and editorial standards for technical and long-form content. The phase-routing model ensures that rework happens at the right level of abstraction: architectural problems go back to the Architect, voice problems go back to the human and Carpenter, and accuracy problems stay with the Judge.
The distinction between the Judge and the Quality Rubric is scope. The Judge works at the line level: detecting weak verbs, unsupported claims, passive voice, and structural inconsistencies within paragraphs. The Quality Rubric works at the piece level: evaluating whether the overall thesis lands, whether the evidence portfolio is sufficient, and whether the piece delivers on its opening promise. A piece can pass the Judge with clean prose and still fail the Quality Rubric because the argument structure does not hold together.
The re-scoring requirement after rework exists to prevent the common failure mode where a fix in one dimension degrades another. Restructuring to improve flow (dimension 3) can weaken the opening hook (dimension 6) if sections are reordered. Re-scoring catches these regression effects before publication.
Content type determines which dimensions are critical. A technical tutorial requires high scores on Technical Accuracy and Structure but may tolerate a lower Voice score. A thought leadership piece requires high Originality and Voice but may tolerate lighter Technical Accuracy. The minimum standards reference file defines these critical-dimension profiles per content type. Applying the wrong profile leads to false passes or unnecessary rework.